This invention relates to secure financial indexing, and more particularly to a distributed computing approach to such indexing that provides security and audit capabilities.
Indexing traded securities (such as for stocks and bonds) was introduced in 1884 by Charles Henry Dow and in 1896 by the Wall Street Journal publishing the Dow index daily. Today multiple trillions of dollars in mutual funds, ETFs, private pools and pension assets either benchmark against or invest according to an index or indexes. There are myriad organizations, such as Standard and Poor's, that develop, manage and publish indexes, and there are thousands of investment firms using indexes for investment or investment benchmarking. Investors use such indexes to look into the past to study the hypothetical performance of the index under various historic scenarios, including actual market conditions as they existed in the past. Investors also use an index to “benchmark” or compare the index to say a mutual fund's actual performance.
Present-day indexes are generally based on published rules whereby individual securities are selected and weighted according to such rules. Until recently, virtually all indexes prescribed investment in stocks or bond portfolios seeking to capture gains only if the respective stocks or bonds grew in value (long-only investing). Security selection in these indexes is prescribed using specific characteristics. For example, the S&P 500 index identifies the 500 largest public companies, by market capitalization, and weights the percentage ownership of shares in each company based on such market capitalization. By contrast, the VIX index uses a more complex set of rules based on options prices to infer future market volatility. These rules are typically spelled out in somewhat plain language and the selection of the securities follow such rules accordingly. Investors are able to take comfort in the assurances by a third party that the rules are sustained and unchanged for each index.
Investors can thus monitor their investment, in say, a mutual fund, to measure actual investment results against the performance of the index as calculated and published by the third-party index manager. Such comparison measurements between actual investment results and the hypothetical performance of the respective index is known in the trade as tracking error.
More valuable to the investor, is that prior to making an investment in a fund, the investor can mimic or benchmark an index. This is known in the trade as a hypothetical back-test of the index. A back-test is generated and published by the index manager using the very same rules and process that governs the selection of securities in the index to look back in time and attendant past data to calculate what the performance of the index would have been in years or decades past. An index allows a potential investor to study the hypothetical performance of the index over time and in different market environments and to compare live performance to the index expectations, or to integrate such performance with other investments to study the impact to an overall portfolio of investments.
The investor trusts a third party (i.e., a party other than the investor or the one who is making money executing the trade for the investor) to certify that the very same rules and tools are consistently applied to calculate back-test index performance as is used for actual performance from the date first used for actual investment.
Most modern indexes are monitored and modified by committee, but only within the rules. Although introducing human discretion to change the make-up of the index may change the securities in the index, that discretion simply applies the rules but does not change them. Introducing changes to the rules will, of course, erode the confidence and veracity of back-testing, as prior published performance results may not have been calculated based on the revised inputs to index performance.
Unlike investment styles that track or benchmark to an index governed by a published set of rules and are judged based on relative performance to the respective index's performance, certain other investment styles seek what is known in the trade as absolute performance, that is, positive performance across multiple market cycles, generally with low correlation to market performance (beta). Interest by investors, both institutional and individual, in absolute-return investment programs has grown substantially since 1980. Proprietary quantitative investment styles constitute a significant and growing portion of the absolute return universe and are very rarely used to create an index because the developer of such quantitative or algorithmic trading strategy must keep his or her trading programs proprietary in order to exact commercial benefit. Third party index calculators will not certify the accuracy of a back-tested performance of an undisclosed quantitative investment method because they have no means of auditing that the rules (generally expressed as software-based algorithms) have not been modified over time. The few indexed quantitative programs, such as the S&P Dynamic VEQTOR Index discloses the mathematics of the program, albeit undiscernible to all but the most mathematically sophisticated.
Excepting a very few indexes that disclose the quantitative rule-book, investors have no reliable, third party-certified means of looking back in time to see how an undisclosed quantitative program may have performed in various market conditions, and no means to track the difference between actual results in a quantitative investment program and expected outcomes. The key to the veracity of any back-test is the certainty that the rules governing the index and the inputs to those rules have not been changed at any time following the calculation of the back-test performance. In other words, there is currently no means for an independent party to stand behind the veracity of back-tested performance based on undisclosed rules.
Various financial industry rules and regulation do not allow for the use and disclosure of back-tested performance as it relates to mutual funds, ETFs or other “retail” investment pools. Private funds on the other hand, for example institutional hedge funds, may develop and disclose back-tested performance of their investment strategies. Therefore, the individual retail investor is generally deprived of any means of studying the hypothetical performance of a contemplated investment over multiple market cycles, particularly if it is new and without a long term track record of its own. This handicap for the retail investor has contributed significantly to the explosion in passive (indexed) investment, particularly as it relates to passive ETFs. While an ETF that follows a published index may not disclose or promote a back-test under the rules, its sponsor can point to the index for the back-test and be judged based on the tracking error to that respective index. Proprietary quantitative investment programs presently have no means of independent certified indexing and thus the retail investor is significantly handicapped vs. the institutional investor if contemplating a proprietary quantitative investment strategy. There is a need to address this conundrum.